Published Online June 2014 in SciRes. http://www.scirp.org/journal/ojap
http://dx.doi.org/10.4236/ojap.2014.32005
How to cite this paper: de Souza, A., Aristones, F., Pavão, H.G. and Fernandes, W.A. (2014) Development of a Short-Term
Ozone Prediction Tool in Campo Grande-MS-Brazil Area Based on Meteorological Variables. Open Journal of Air Pollution, 3,
42-51. http://dx.doi.org/10.4236/ojap.2014.32005
Development of a Short-Term Ozone
Prediction Tool in Campo Grande-MS-Brazil
Area Based on Meteorological Variables
Amaury de Souza*, Flavio Aristones, Hamilton Germano Pavão, Widinei Alves Fernandes
Institute of Physics, Federal University of Mato Grosso do Sul, Campo Grande, Brazil
Email: *amaury.de@uol.com.br
Received 6 March 2014; revised 12 April 2014; accepted 18 April 2014
Copyright © 2014 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/
Abstract
The objective of this study was to develop a model to predict the concentration of ozone. The
measurements of ozone were conducted at the Federal University of Mato Grosso do Sul. The
predictor variables related to climate were supplied by Embrapa Gada de Corte. Analyses of the
data show a strong correlation between ozone and wind speed (0.75), humidity (−0.64) and
temperature (0.41), as the factors that affect levels of concentration ozone. The observed and
predicted values of daily ozone had a correlation coefficient (R) of 0.69.
Keywords
Regression Model, Meteorology, Ozone Prediction
1. Introduction
Studies on the influence of air pollution on the quality of human life have been conducted with great intensity in
recent years [1]-[11]. This study aimed to evaluate the effects of variables that affect air quality, and of which,
some made a direct link between air pollution with mortality rates and respiratory diseases.
Atmospheric pollution is characterized basically by the presence of toxic gases and solid particles in the air.
The main causes of this phenomenon are the disposal of certain types of industries (steel, petrochemicals, cement,
etc.) and the burning of coal and oil in power plants, automobiles and domestic heating systems [2]
[12]-[15].
http://dx.doi.org/10.4236/ojap.2014.32005
How to cite this paper: de Souza, A., Aristones, F., Pavão, H.G. and Fernandes, W.A. (2014) Development of a Short-Term
Ozone Prediction Tool in Campo Grande-MS-Brazil Area Based on Meteorological Variables. Open Journal of Air Pollution, 3,
42-51. http://dx.doi.org/10.4236/ojap.2014.32005
Development of a Short-Term Ozone
Prediction Tool in Campo Grande-MS-Brazil
Area Based on Meteorological Variables
Amaury de Souza*, Flavio Aristones, Hamilton Germano Pavão, Widinei Alves Fernandes
Institute of Physics, Federal University of Mato Grosso do Sul, Campo Grande, Brazil
Email: *amaury.de@uol.com.br
Received 6 March 2014; revised 12 April 2014; accepted 18 April 2014
Copyright © 2014 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/
Abstract
The objective of this study was to develop a model to predict the concentration of ozone. The
measurements of ozone were conducted at the Federal University of Mato Grosso do Sul. The
predictor variables related to climate were supplied by Embrapa Gada de Corte. Analyses of the
data show a strong correlation between ozone and wind speed (0.75), humidity (−0.64) and
temperature (0.41), as the factors that affect levels of concentration ozone. The observed and
predicted values of daily ozone had a correlation coefficient (R) of 0.69.
Keywords
Regression Model, Meteorology, Ozone Prediction
1. Introduction
Studies on the influence of air pollution on the quality of human life have been conducted with great intensity in
recent years [1]-[11]. This study aimed to evaluate the effects of variables that affect air quality, and of which,
some made a direct link between air pollution with mortality rates and respiratory diseases.
Atmospheric pollution is characterized basically by the presence of toxic gases and solid particles in the air.
The main causes of this phenomenon are the disposal of certain types of industries (steel, petrochemicals, cement,
etc.) and the burning of coal and oil in power plants, automobiles and domestic heating systems [2]
[12]-[15].
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